CommonClimate
commented
3 months ago Thank you for the suggestion @DStamatis. We'll look at feasibility in our next development meeting and see if we can implement quickly. I can imagine an argument, y_minor_ticks = False by default, but if set to True, it would label the axes as per the current Pyleoclim style (e.g. journal, notebook, or other). It won't make sense for large stacks (what stackplot was designed for), but for a small one like this, it would add value.
DStamatis
Is your feature request related to a problem? Please describe. I am experiencing some frustration with the stackplot command in pyleoclim. While it is extremely useful for quickly visualizing information from different datasets, it currently lacks the ability to add minor ticks on the y-axis for each dataset. This feature would significantly enhance the clarity and detail of the final plot.
Describe the solution you'd like I have considered using the plot function along with the twinx command from matplotlib. However, this approach is limited to datasets with similar values and only works for up to four different datasets. For stackplots with five or more datasets, a more complex solution involving the subplot command might be required, which is not ideal.
Describe alternatives you've considered Perhaps the plot function can be used, with the twinx command from matlolib, but that would only work for four different datasets with similar values. For stackplots with 5 or more datasets something more complicated might work with the subplot command.
Additional context ts_final = [benthic,CO2,dD,MIS7_1_series,MIS7_series] ms_final = pyleo.MultipleSeries(ts_final)
fig, ax2 = ms_final.stackplot(figsize=[5, 10], savefig_settings=None, xlim=None, fill_between_alpha=0, colors=None, cmap='tab10', norm=None, spine_lw=1.5, grid_lw=0.5, label_x_loc=-0.15, v_shift_factor=0.75, linewidth=1.5)
Highlighting interstadial 7d and 6e
ax2=pyleo.utils.plotting.make_annotation_ax(fig, ax2, ax_name = 'highlighted_intervals', zorder=-1) intervals = [[185, 191], [225, 235]] ax2['highlighted_intervals'] = pyleo.utils.plotting.hightlight_intervals(ax2['highlighted_intervals'], intervals, color='grey', alpha=0.3)
Marking Interstadial boundaries
ax2=pyleo.utils.plotting.make_annotation_ax(fig, ax2, ax_name = 'interstadials', height=.03, loc='above', v_offset=.015,zorder=-2) ax2['interstadials'].set_facecolor((1, 1, 1, 0))
inter_intervals_pairs = [[185, 191], [191, 205], [205, 215], [215, 225], [225, 235], [235, 243]] inter_labels = ['6e', '7a', '7b', '7c', '7d', '7e'] ax2['interstadials'].set_ylim([-1,0])
colors = ['red', 'navy', 'orange', 'violet', 'green', 'aqua'] ax2['interstadials'] = pyleo.utils.plotting.hightlight_intervals(ax2['interstadials'], inter_intervals_pairs, color=colors, alpha=.2)
interstadials (labels)
ax2=pyleo.utils.plotting.make_annotation_ax(fig, ax2['interstadials'], ax_name = 'interstadial_annotation', zorder=1, v_offset=0.01, height=0, loc='above')
x_locs = [np.mean(interval) for interval in inter_intervals_pairs] ax2['interstadial_annotation'].set_ylim([0,3]) ax2['interstadial_annotation'] = pyleo.utils.plotting.label_intervals(fig, ax2['interstadial_annotation'], inter_labels, x_locs, orientation='north', baseline=.45, height=0.35, buffer=0.1, linestyle_kwargs= {'color':'gray'}, text_kwargs={'fontsize':10, 'va':'bottom'})